Results for “anki-connect”

Authenticate, initialize, and use the stateful Gemini Interactions API for multi-turn conversations, streaming, structured output, and function calling on the Gemini Enterprise Agent Platform.

Coordinate agents via the AMQ CLI for file-based inter-agent messaging. Use this skill whenever you need to send messages to another agent (codex, claude, or any named handle), check your inbox, drain queued messages, set up co-op mode between agents, join a swarm team, route messages across projects, or diagnose delivery issues. Also use it when you receive a message and need to know how to reply, inspect receipts, or handle priority. Covers any multi-agent coordination task where agents need to talk to each other — review requests, questions, status updates, decision threads, wake notifications, and orchestrator integration (Symphony, Kanban). For collaborative spec/design workflows specifically, prefer the /amq-spec skill which provides structured phase-by-phase guidance. Not intended for distributed systems design (RabbitMQ, Kafka), CI/CD pipelines, or single-agent tasks with no partner.

Manages and analyzes Ably real-time messaging resources, covering channels, presence, connections, usage analytics, and account health via REST and Control APIs.

Apache Kafka event streaming platform. Covers producers, consumers, topics, partitions, Kafka Streams, and Connect. Use for high-throughput event-driven architectures and real-time data pipelines. USE WHEN: user mentions "kafka", "event streaming", "kafka streams", "consumer groups", "topic partitions", asks about "high throughput messaging", "event sourcing", "log aggregation", "real-time pipelines" DO NOT USE FOR: simple queues - use `rabbitmq` or `activemq`; cloud-native lightweight - use `nats`; AWS-native - use `sqs`; Azure-native - use `azure-service-bus`; GCP-native - use `google-pubsub`

Build streaming data pipelines with Redpanda Connect using declarative YAML configs, Bloblang mappings, and component discovery. Covers running, linting, and dry-running pipelines.

Operate Redpanda through its Kafka-compatible API: produce and consume records, manage topics and consumer groups, run transactions, and configure tiered storage using rpk and Kafka clients.

Diagnoses and validates Redpanda Connect pipelines using linting, dry-run connection tests, logging, metrics, tracing, and health endpoints, including enterprise feature troubleshooting.

Runs an autonomous multi-agent software development pipeline that takes a PRD through to production with zero human intervention, using model-tiered agents, memory, and verification cycles.